Climate Change Climate change scenarios of the 21st century: Model simulations Climate Change Oliver Elison Timm ATM 306 Fall 2016 Lecture 8 1

Climate change simulations Objectives: Provide an overview on how climate scientists simulate the future climate Overview about climate models Hierarchy of climate models Coupled atmosphere-ocean general circulation models Climate forcing: Radiative forcing concept Representative Concentrations Pathway (RCP) Climate sensitivity Feedbacks in the climate system

SIRF course evaluation Please take a moment and fill out an online course evaluation for this ATM306 course. Thank you! The SIRF web page will be open Nov 21st- Dec 13th (reading day) http://www.albany.edu/ir/onlineSIRF-FAQ.html

Numerical simulation of climate: increase in models’ grid resolution Over the last 30 years the complexity of climate models has increased from about 500km x 500km horizontal resolution to about 100km x 100km resolution. The number of vertical levels increased, too. First IPCC report (1990)

Numerical simulation of climate: increase in models’ grid resolution Typical grid resolution of climate models used in the second IPCC report (1996)

Numerical simulation of climate: increase in models’ grid resolution IPCC AR5 report (2013): the higher resolution models have about 100 km x 100 km resolution)

general circulation models (GCM) Increase in spatial resolution 1990 2013 2000 latest 2007

Numerical simulation of climate The name “General Circulation Model” (GCM) is used for atmospheric climate models, global ocean models, and coupled atmosphere-ocean models Key to the numerical simulation: Mathematical representation of the climate based on physical, biological and chemical principles. Numerical integration using discretized approximations to the mathematical equations. Gridded set of representative spatial points, and a discrete time integration step.

How many grid points do you have in a model with 100km X 100km resolution and 20 vertical levels ? With finer grid spacing, the time stepping must be become finer, too. Climate models use integration steps now as short as a few minutes from one step to the next in the simulation!

How many grid points do you have in a model with 100km X 100km resolution ? If the average grid point spacing is 100km apart from the neighboring grid points, it represents an area of 100km*100km = 10,000 km2 = 1010 m2 Earth area is 510,072,000 km2 = 5.10*1014 m2 ~ 50,000 horizontal grid points With 20 vertical levels => ~ 100,000 grid points For a doubling of grid resolution it takes 10 times more computing (CPU) time. With finer grid spacing, the time stepping must be become finer, too. Climate models use integration steps now as short as a few minutes from one step to the next in the simulation! Notes: For comparison: one NFL football field is about 5,000 m2 NY State has 141,300 km2 (data from Wikipedia) One grid point represents temperature, winds, humidity for this area (air volume)

Improved climate model resolution supported by technological development Computer power increase supports increasing climate model resolution From Wikipedia: Moore’s Law

Example of modern computational methods: Nonhydrostatic Icosahedral Atmospheric Model (NICAM) Grid designs that avoid pole singularity, and allow for equal fine-scale resolution around the globe. http://www.jamstec.go.jp/e/hot_pictures/ Satoh et al, J. Computational Physics, 2008 12

Nonhydrostatic ICosahedral Atmospheric Model (NICAM) convective cloud processes 3.5km horizontal resolution, 10^9 nodes, 15s time step http://www.jamstec.go.jp/e/hot_pictures/ Satoh et al, J. Computational Physics, 2008 13

resolution GCM: Clouds in GCM and from satellite observations Example from NICAM 3.5 km resolution GCM: Clouds in GCM and from satellite observations Snapshot: 31 December 2006 Earth Simulator simulation at 3.5-km resolution compared with Infrared image from the Multi-Functional Transport Satellite (MTSAT-1R) → which one is which? → more realistic cloud-resolving simulations will become possible in near future! (currently it is too costly to simulate a 100 years into the future Miura et al., 2007 14

Example of high-resolution ocean modeling Coupled atmosphere ocean models resolve now eddies in the ocean (0.1 degree resolution) Link to GFDL animation

Numerical simulation of climate For each grid point dynamical equations (acceleration forces acting on the air/ ocean parcels) must be computed In addition physical processes must be calculated: Heating/cooling rates by radiation, heat advection (by winds) Hydrological processes: rainfall, evaporation, cloud processes (and chemical reactions) Sea ice formation, or melting and sea ice transport Momentum, heat, mass exchanges at the interfaces between ocean-ice-land-atmosphere Figure from Neelin

Numerical simulation of climate Besides the numerical resolution, a better representation of physical and chemical processes is developed: Simple ‘swamp’ oceans were replaced by fully 3-dimensional ocean circulation models (including sea ice) Atmospheric chemistry (e.g ozone, aerosols) is now simulated Some models have dynamic vegetation together with more sophisticated land-atmosphere-vegetation interactions A few models (Earth system models) include now an active ocean carbon cycle (chemical + biological processes) Ice sheet models are still in progress to be fully coupled and implemented into the next generation climate models.

Numerical simulation of climate land ice (Greenland, Antarctica, glaciers)

Application of climate models: Development, testing, and climate scenario simulation Observations are of utmost importance for development, testing (validation) of climate models http://www.climate.be/textbook

Representation of land vegetation in a climate model http://www.climate.be/textbook

Representation of sea ice in a climate model http://www.climate.be/textbook

Processes involved in ice-sheet modeling (1) Surface Mass Balance: Accumulation – Ablation (surface melting - refreezing) (2) Flow of the ice (3) Ocean-ice interface: floating ice, melt rates, calving http://www.climate.be/textbook

GCMs Atmosphere and Ocean models have to solve two different type of problems: Dynamical processes: The dynamic behavior of the fluid (atmosphere, or ocean): winds / currents, wave propagation, advective processes; governed by fundamental physical laws (momentum, thermodynamics) Grid resolution and time step scheme resolve the most important aspects of the fluid dynamics Physical parameterizations: The method of incorporating ‘unresolved’ processes that happen inside the grid boxes. These fine-scale processes are represented by some functions that depend on the modeled grid-averaged values (e.g. temperature, humidity). These equations are guided by both theory and empirical (observations) studies. For example different types of cumulus convection, and rain production have been developed for climate models.

Terrestrial vegetation How to simulate historical and future climate trends with GCMs? Forcing: External factors with impact on the climate, which can change with time during the climate simulation: Anthropogenic or natural: Greenhouse gas concentrations, aerosols Human-induced land cover change Volcanic eruptions Solar cycle Climate model components Atmosphere Terrestrial vegetation Air-Land fluxes albedo Marine carbon cycle CO2 fluxes air-sea fluxes Ocean Boundary conditions: Constant conditions (e.g prescribed ice-sheets on land, solar constant)

Representative Concentration Pathways (RCPs) “The goal of working with scenarios is not to predict the future but to better understand uncertainties and alternative futures, in order to consider how robust different decisions or options may be under a wide range of possible futures”. Source: IPCC Scenario Process for AR5 Note: a good introduction to RCPs is “The Beginner's Guide to Representative Concentration Pathways” which you can find on: http://www.skepticalscience.com/rcp.php

Representative Concentration Pathways Notes: RCP#.# : The number indicates the radiative forcing by the year 2100 that is induced by all forcing factors (greenhouse gases, aerosols, land cover change). Positive numbers indicate a net energy gain for the Earth’s climate system. Note: SRES are earlier scenarios (IPCC SPECIAL REPORT EMISSIONS SCENARIOS)

Four pathways to represent a multitude of alternative future scenarios Carbon dioxide emissions are the most important among the greenhouse gas emissions now and in near future In order to make climate model scenarios comparable and impacts studies feasible, four scenarios were selected that cover the wide range of scenarios.

Other greenhouse gas emissions in the four RCPs X Climate models simulate water vapor concentrations => Not an external forcing

Greenhouse gas emissions in the four RCPs Note: Other gases in the family of Halocarbones and Chlorofluorocarbons are considered

Air pollutants emissions in the four RCPs sulfur dioxide nitrogen dioxide (nitric oxide)

What determines the different emissions scenarios? CO2 emissions 2000-2100 Figure shows annual CO2 emissions out to 2100 associated with each RCP RCP2.6: optimistic (complete phase-out of CO2 emissions by 2070 and negative flux of CO2 afterward (we would actively be pulling CO2 out of the air through mitigation) RCP8.5 pessimistic: scenario where CO2 levels soar to >1300 ppm by 2100 and continue to rise. Unrealistic (?) as we may not be able to produce enough oil, coal and gas to emit that much CO2. What determines the different emissions scenarios? Inman, Nature Climate Change, 2011

RCPs consider different world populations, and economic growth and technology development that are consistent with the GHG emissions Gross Domestic Product (representative global average) World Population

RCPs distinguish between different mixes in primary energy sources.

Kaya factors / Kaya Identity RCPs allow a more detailed look at the future pathways and track the effects from population, development, technologies and productivity in their role for greenhouse gas emissions F global CO2 emissions from human sources P global population G world GDP E global energy consumption G/P economic production E/G energy intensity (depends on production goods and technology) F/E carbon efficiency (primary energy sources, carbon sequestration) See Wikipedia for more info, or https://www.e-education.psu.edu/meteo469/node/213

The resulting greenhouse gas concentrations for the RCPs are used as external forcing